{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Text and Annotation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Creating a good visualization involves guiding the reader so that the figure tells a story.\n",
    "In some cases, this story can be told in an entirely visual manner, without the need for added text, but in others, small textual cues and labels are necessary.\n",
    "Perhaps the most basic types of annotations you will use are axes labels and titles, but the options go beyond this.\n",
    "Let's take a look at some data and how we might visualize and annotate it to help convey interesting information. We'll start by setting up the notebook for plotting and  importing the functions we will use:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "plt.style.use('seaborn-whitegrid')\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example: Effect of Holidays on US Births\n",
    "\n",
    "Let's return to some data we worked with earler, in [\"Example: Birthrate Data\"](03.09-Pivot-Tables.ipynb#Example:-Birthrate-Data), where we generated a plot of average births over the course of the calendar year; as already mentioned, that this data can be downloaded at https://raw.githubusercontent.com/jakevdp/data-CDCbirths/master/births.csv.\n",
    "\n",
    "We'll start with the same cleaning procedure we used there, and plot the results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.chdir(\"/home/lab466/pythons/pyDSHandbook3/notebooks\")\n",
    "births = pd.read_csv('data/births.csv')\n",
    "\n",
    "quartiles = np.percentile(births['births'], [25, 50, 75])\n",
    "mu, sig = quartiles[1], 0.74 * (quartiles[2] - quartiles[0])\n",
    "births = births.query('(births > @mu - 5 * @sig) & (births < @mu + 5 * @sig)')\n",
    "\n",
    "births['day'] = births['day'].astype(int)\n",
    "\n",
    "births.index = pd.to_datetime(10000 * births.year +\n",
    "                              100 * births.month +\n",
    "                              births.day, format='%Y%m%d')\n",
    "births_by_date = births.pivot_table('births',\n",
    "                                    [births.index.month, births.index.day])\n",
    "births_by_date.index = [pd.datetime(2012, month, day)\n",
    "                        for (month, day) in births_by_date.index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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+DlbKkctEKYUgCMK4U99pYmdVNx8VNw87RMPqcNJtdfisSfVMcivwMcmt02jz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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f090c1bf0b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 4))\n",
    "births_by_date.plot(ax=ax);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we're communicating data like this, it is often useful to annotate certain features of the plot to draw the reader's attention.\n",
    "This can be done manually with the ``plt.text``/``ax.text`` command, which will place text at a particular x/y value:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sJs9rtZKP6Ohonn76aXbv3o1Op+O1117js88+o7q6mnnz5gEQFhbGa6+9xrJl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Zpm/Y9MCHHzlZeX4+fnh9ls5scff8RisdS5f2RkJPfddx/JycnYbDb27t2LWq1mwIABREREUFBQ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\nMjIyqKysZOTIkSxdurTKa6tXr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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f08dafd7358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 4))\n",
    "births_by_date.plot(ax=ax)\n",
    "\n",
    "# Add labels to the plot\n",
    "style = dict(size=10, color='gray')\n",
    "\n",
    "ax.text('2012-1-1', 3950, \"New Year's Day\", **style)\n",
    "ax.text('2012-7-4', 4250, \"Independence Day\", ha='center', **style)\n",
    "ax.text('2012-9-4', 4850, \"Labor Day\", ha='center', **style)\n",
    "ax.text('2012-10-31', 4600, \"Halloween\", ha='right', **style)\n",
    "ax.text('2012-11-25', 4450, \"Thanksgiving\", ha='center', **style)\n",
    "ax.text('2012-12-25', 3850, \"Christmas \", ha='right', **style)\n",
    "\n",
    "# Label the axes\n",
    "ax.set(title='USA births by day of year (1969-1988)',\n",
    "       ylabel='average daily births')\n",
    "\n",
    "# Format the x axis with centered month labels\n",
    "ax.xaxis.set_major_locator(mpl.dates.MonthLocator())\n",
    "ax.xaxis.set_minor_locator(mpl.dates.MonthLocator(bymonthday=15))\n",
    "ax.xaxis.set_major_formatter(plt.NullFormatter())\n",
    "ax.xaxis.set_minor_formatter(mpl.dates.DateFormatter('%h'));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ``ax.text`` method takes an x position, a y position, a string, and then optional keywords specifying the color, size, style, alignment, and other properties of the text.\n",
    "Here we used ``ha='right'`` and ``ha='center'``, where ``ha`` is short for *horizonal alignment*.\n",
    "See the docstring of ``plt.text()`` and of ``mpl.text.Text()`` for more information on available options."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transforms and Text Position\n",
    "\n",
    "In the previous example, we have anchored our text annotations to data locations. Sometimes it's preferable to anchor the text to a position on the axes or figure, independent of the data. In Matplotlib, this is done by modifying the *transform*.\n",
    "\n",
    "Any graphics display framework needs some scheme for translating between coordinate systems.\n",
    "For example, a data point at $(x, y) = (1, 1)$ needs to somehow be represented at a certain location on the figure, which in turn needs to be represented in pixels on the screen.\n",
    "Mathematically, such coordinate transformations are relatively straightforward, and Matplotlib has a well-developed set of tools that it uses internally to perform them (these tools can be explored in the ``matplotlib.transforms`` submodule).\n",
    "\n",
    "The average user rarely needs to worry about the details of these transforms, but it is helpful knowledge to have when considering the placement of text on a figure. There are three pre-defined transforms that can be useful in this situation:\n",
    "\n",
    "- ``ax.transData``: Transform associated with data coordinates\n",
    "- ``ax.transAxes``: Transform associated with the axes (in units of axes dimensions)\n",
    "- ``fig.transFigure``: Transform associated with the figure (in units of figure dimensions)\n",
    "\n",
    "Here let's look at an example of drawing text at various locations using these transforms:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f08db031f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(facecolor='lightgray')\n",
    "ax.axis([0, 10, 0, 10])\n",
    "\n",
    "# transform=ax.transData is the default, but we'll specify it anyway\n",
    "ax.text(1, 5, \". Data: (1, 5)\", transform=ax.transData)\n",
    "ax.text(0.5, 0.1, \". Axes: (0.5, 0.1)\", transform=ax.transAxes)\n",
    "ax.text(0.2, 0.2, \". Figure: (0.2, 0.2)\", transform=fig.transFigure);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that by default, the text is aligned above and to the left of the specified coordinates: here the \".\" at the beginning of each string will approximately mark the given coordinate location.\n",
    "\n",
    "The ``transData`` coordinates give the usual data coordinates associated with the x- and y-axis labels.\n",
    "The ``transAxes`` coordinates give the location from the bottom-left corner of the axes (here the white box), as a fraction of the axes size.\n",
    "The ``transFigure`` coordinates are similar, but specify the position from the bottom-left of the figure (here the gray box), as a fraction of the figure size.\n",
    "\n",
    "Notice now that if we change the axes limits, it is only the ``transData`` coordinates that will be affected, while the others remain stationary:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xZGVlccUVV7B+/fpay9rtdr755hvWrVvH6tWrWbx4cb3bPXz4MO+//z5ZWVm8+uqrpKSk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\n/wcj7gHa++AVPAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f08db031f98>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.set_xlim(0, 2)\n",
    "ax.set_ylim(-6, 6)\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This behavior can be seen more clearly by changing the axes limits interactively: if you are executing this code in a notebook, you can make that happen by changing ``%matplotlib inline`` to ``%matplotlib notebook`` and using each plot's menu to interact with the plot."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Arrows and Annotation\n",
    "\n",
    "Along with tick marks and text, another useful annotation mark is the simple arrow.\n",
    "\n",
    "Drawing arrows in Matplotlib is often much harder than you'd bargain for.\n",
    "While there is a ``plt.arrow()`` function available, I wouldn't suggest using it: the arrows it creates are SVG objects that will be subject to the varying aspect ratio of your plots, and the result is rarely what the user intended.\n",
    "Instead, I'd suggest using the ``plt.annotate()`` function.\n",
    "This function creates some text and an arrow, and the arrows can be very flexibly specified.\n",
    "\n",
    "Here we'll use ``annotate`` with several of its options:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VxiK2J1cHBgqqX4fxS/fy6e/HDcmh6zoLfv6DyV8fpFsLb5aP62J3d9EarepX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\nx/4fWKYtt6LD4aIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f08d958ba20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "x = np.linspace(0, 20, 1000)\n",
    "ax.plot(x, np.cos(x))\n",
    "ax.axis('equal')\n",
    "\n",
    "ax.annotate('local maximum', xy=(6.28, 1), xytext=(10, 4),\n",
    "            arrowprops=dict(facecolor='black', shrink=0.05))\n",
    "\n",
    "ax.annotate('local minimum', xy=(5 * np.pi, -1), xytext=(2, -6),\n",
    "            arrowprops=dict(arrowstyle=\"->\",\n",
    "                            connectionstyle=\"angle3,angleA=0,angleB=-90\"));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The arrow style is controlled through the ``arrowprops`` dictionary, which has numerous options available.\n",
    "These options are fairly well-documented in Matplotlib's online documentation, so rather than repeating them here it is probably more useful to quickly show some of the possibilities.\n",
    "Let's demonstrate several of the possible options using the birthrate plot from before:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8Y/UdHKvv4Bv/2sY1/9jKKztKe/rvL28hOymS2PDgnrashAiyEsL5/GiDz3nt\nPK6tx6Snqbtl0XhEajSPvn84IN1mIGgGdf95pafosg+AjLjhk3wATE/VDPpTufOgUJwKVruD/KpW\nZoyJ7bmz09nd/90zZVArFAqFohcnNLe6QZ0WQ0lDp99I95pWMzmpmmF2yYw0atu62VPa1O85qw9V\nExsezKKJiXx1Zjpr82toM1u99j1c1UqHxc48vSgJwHkihdq2br8G/8/fO4isaePpm+bw0T1LyU6O\n5O/rjgJw2Yx04ERg4o5jjTyz8ShXnTmG1JiwnoIoG47UccWTmzlU2UpcRDAbj5ww+PaXNffop91Z\nlJ3EtuIGr7eL28yaF/YMt/OCTUZ+ccU0Kpq7eHvv4GT8aGi39OuhBhD6+xYfEexTGvJFkREdxJS0\naF7bWTboAZoKRSAU1rRjsTmYPiaWyFAtB7XyUCsUCoViQPQY1C4Pte69lDW+jVa7w6nprvXbo+dP\nSSHEZOSjfmQfnRYbn+bXsmxKCkEmI5fOSO9XE+1KbeduUC/NSQZgU6Fvqch7+yt5fVc5d503iXOF\ndq0fXyQALTfz7HHxgOahbumyct9re8lKiOBXX5sOwHi9IMqfPpEAfHD3Ei6Znsb24gZsdgfVLWZq\n27qZmRnrce1FkxJpNds47CXQ8EBFC04nHuctyE5gSlo0r2wvHRSD0hVg2h+T9fd4qEqODwSDwcAt\ni8ZTUN3GrpL+N2QKxVDgyjg0Y0wskfoG059DQRnUCoVCoejFCYNaM45z07VMHy6NrTcaOzTdtctw\niw4LZmlOEqsOVvk0Cp//vISWLis3LhgHwOxx8USGmNhU6NugHpsQQWrMCUlCWmwYOSlRPs+pbTPz\nyLsHOSMrjnuX5fS0XzQtjcWTElmWm0pYsImkqFAqmrr4MK+KyhYzf7p2FlGh2g9pWLCJMXHhOJzw\nh+UzGZcYycKJSbR12zhU2cp+XT89M9OLh3piEkFGA//ZXOxxbH+ZZyAjaAbljfPHcqiytVcu7JOh\nJ8DUTylxVzaX4dZPu7jyjAyiw4J4YevpV1RIMfo5UNFCVGgQ4xMjiXB5qJXkQ6FQKBQDob7dQmiQ\nscegHBMXTmpMKKsO+vY2N3RoRnhi5AlP6CUz0qlsMbPfi1HYZrby9MajnCuSmaN7iINNRhZkJ7LZ\ni4fa6XSy83hjj37anaU5yew41ojZaufFrcfZdLy955yH3j5Ip8XOH6+dRZBbVT6DwcBLt8/nt1fP\n0NYYH04y5UE2AAAgAElEQVRFcxebCutIjw3rmZOLG+aP5X8unMzF0zV5yEI9d/OWo/W8tqNUDyyM\n8ZhbcnQoPzhvEu/sq+wpEuFif1kz4xIjiPdi7F555hjCg028sr3U49hAcAWY+vNQJ0SGIFKjmTHG\n08s+HESEBHHtnCw+PlAVcMVJhWKwOFDRwvQxMRiNhp7vQeWhVigUCsWAqG/TskIYDFqgnNFo4OaF\n49lUWO+z8t+JQMYTxuGFuakEGQ187KWa4XNbjtPcaeX+Cyb3al+Sk0RJQydlfQrJlDR00tRp5azx\nvQ1dgKU5SXTbHDz5WREPv3uIF/dpMoGC6jY+OVzDvctymJQS5XGea30AY+LCKG3sZEtRPUtzknod\nA62q4N1uHu7k6FBEajTPf36cdbKOu8+fRFiwyetrc+d5E8lJieJnbx/olc82r7zZq1cbICYsmCtm\nZfDe/kpaurxrygOhb4Bpf3x4zxLuWTbppK812Fw3Nwubw+mxEVEohhKr3cFhPSAR6IkpUBpqhUKh\nUAyIOi+a2xvnjyU82ORVugBuHmo3wy02IpiFExNZdbDaQ/axcm8FS3OSPAL5luYkAXhIOFyyir7y\nCID52QkEmww9VQnLWqzUtpp7dNXXzM7sf8FoXvjSxk5azbYeXbY/Fk5MpKa1m6yEcG5ZNN5nv9Ag\nE49eOY2qFjNr9ewhta1mKlvMzPKiu3Zx86JxdFntrNipealLGjoobwqsYqUL1/sSiEEdZDJ6bCSG\nk8mpUSRGhrC9uHc+85ZOKw26LEmhGGzcAxKBHg91p58CUsqgVigUCkUv6tstJPdJsxYXEcLyOZm8\ns7fS6y34+nZPDzXApTPSKWno5LCb/rrLYud4Q4eHrAJgYnIUaTFhbC7qHWS4r6yZ8GATk1M9Pc0R\nIUHMGRePwQAPf3UqoBVM2VzUQE5KFGkBVP4bo2uHDQZYPCnJb3+Ac4RmeP/0klxCg7x7p10smJBI\nUlQIn+neVpcMxltmEBfTMmJZmJ3Ic1uOU9HcxVVPfc6Dbx0IaG4u+urhRxIGg4F5ExLY7laGvMti\n52tPbeHyJzYHVL1OoRgoBytPBCQCbhpq5aFWKBQKxQDwVQjklkXjsdgdXgu21Ld3E2Q09MrDDPCV\nqakYDfTSXxfWtuF0nkjV5o7BYGBJThIbj9Tzzt4KLDateMq+smZmjIntpYN256eX5PK368/k1kXj\niQw2skHWseNYQ8DG8Zj4CED7EU3wE8Dn4tzJyax94Bwu1dPu9YfRaOCcySmsl7XY7A72ljZhMhq8\n6q7duWPpBCpbzFz91BYaOyyUDdBD3SP58KOhPl2ZPyGBiuauHs/8nz6RHKvvoKrVzB9Xy2GenWI0\nUt7UhcEA4/TsPhHBKihRoVAoFG5Y7Q7qOmw0tHf7zLzhcDhp7PCet3hSShSZ8eFs9VKopKG9m8So\nEA/JQGJUKPMnJPLRgRM6apcOe3Kap0ENmhGZGhPKfSv2cd0zW+m22TlU2cqsLN/yiFlZcVwxKwOT\n0cCMtDDe21+J2erokZD4w+WhDrQ/aMa/N222L86fkkKr2camwnpW7CxjYXai35zP54kUspMiqWnt\nZnxiBFUt5gGl0qtv7yYkyEh06PDmlj5Z5k3Qgj93HGtkd0kT/9lyjBvnj+XmBeN4futx9vrJc65Q\nDJSmDgtx4cE9xZaCTEbCgo1+NdRD9hcmhDgXeAM4pDcdAH4PvAiYgCrgJilltxDiRuA+wAE8I6X8\njxAiGHgOGAfYgduklN7FewqFQqHwy/+8vp/39lcCpdy2eDw/v3yaR5+mTgt2h9OnRGBhdiKfHK7B\n4XBiNJ4wnvsrHnLJjDQeefcQhTVt5KRGc6SmjZAgY09+575MSYthzf3n8PzW4zz6/mH+trYQi83R\nrzzCnZlp4Wwr6yTIaGC+no3DH5NTo/jO2dncMH9cQP1PhqWTtRR6P3pzPw0dFn6k58LuD6PRwO+X\nz2RfWTNGg4FffnCYpk7vQYp93xPQ9fCRnhudkcKUtGhiwoL45FANBytbyIgN56eX5uJ0Oll1qJrH\nVxXw2ncWDvc0FaOIxk6LR+adyJCgYZd8bJBSnqv/uxv4JfB3KeVSoAj4lhAiEngEuAA4F7hfCJEA\n3AA0SymXAL8GfjvEc1UoFIpRS2OHhY8PVrEwK4LspEivhUbATQvtQyKwaFIiLV3WXppo7bzuXgGJ\n7lw0TSvt/bEu+yiobiMnJarHA+QNV2aR7ORI/rFBq2h4RoAG9Rlpmmb6zLFxPQFF/ggyGfnZpbk9\nnuqhICYsmLPGx1PfbuGyGekBbxDOGp/AHUuzSde14NUtvTXsZY2d3PrfHcx+bA0tfYzt+nbLiJV7\ngPY5mDchgVWHqqlpNfP3G2cTFRpEdFgw31o8gW3FjRyqPLVc3QqFO00dFhIi+hjUoUGnXVDiucB7\n+uP30Yzo+cBOKWWLlLIL2AIsBpYBb+t91+ptCoVCoTgJ3ttXgdXu5KYz4snNiKG2zXuWhL5VEvuy\nMFuTRPSVfdS3+y4ekhoTxlnj4ntkH0dq2rzqp/tiMhq4+/xJWh7lqJCAjd1x8SHMzIzla2eOCaj/\nF8mlM9IJDTLywwC8031xBVdWt3b1tO0uaeLCv2xgS1E9zZ1Wthb3fl8afOjhRxIL9LsMD102tdem\n6vp5Y4kIMfGfzceGa2qKUUhjh6eHOiLE5DcIdqhFVVOFEO8BCcCjQKSU0vUtXgukA2mAezi3R7uU\n0iGEcAohQqSUFvcL5OfnYzabyc/PH+KlDC+jaY2jaS2+GM1rHM1rczEa1/jSlnImJYSQHuEk2NpB\ndXOn1zXuL9aKorTWlpPf7T3/b2ZMMJ/sP86SZO3r3Ol0UtdmxmBp9/m6zU018o8dbfz3k13UtHYT\nb+wK6DXOCXEyNjaY8fHBFBQUBLRWS3c3jy9LBLyvcTiZE+vk+WuyMNeVku+7WrpX2ju0H/S9BceJ\nHxfCnrxD3PleObGhRn77lXS+/145H+4qZJxJ0xU7nU4qGjsYE+E87V6H/uj79zcn1sGjy9KYG+f5\nfl6QHcl7+yq4eqKJxIiRoxMfjd8xLkb62upaOhkXTa81GO0W6ppsgO84jqH89BWiGdGvA9nAuj7X\n83Wvb0Dtubm55Ofnk5ube7LzHBGMpjWOprX4YjSvcTSvzcVoW2N+VStFjcU8esU0wsK6mDI+hnfy\nC8jKzvGQRGypLwZqmT9zKrERwV7HO6fAxjt7K5g0WRBsMtLebcNiP8bksenk5k70es74iXbeOPwZ\nT+3U8kkvmTmRXJES0Pw/nJhDkNFIeEj/qel61jvK3j8XNrsD41ulEBFHWJiDF/Jt1HTYWPGdhcyb\nkMD8g2YKGrt61r67pIlm8zEuOGMCublZwzz7wPH2/p3po+//pHTw/h/Xs6c5jHvm5PjodfoxWj+j\nMLLX5nQ6abMcZ0JGCrm5U3rak7a2+S2wNGSSDyllhZRyhZTSKaU8ClQD8UII1z27MUCl/i/N7VSP\ndj1A0dDXO61QKBQK/6w6WI3RAFfMygAgNUaTANS0euaTbu60YjRATLhvf8viSUl0WOzsLtE8oQ1+\nZCIA4SEmvnfOROp0qckUHxk+vBEdFhywMT2aCTIZSYkOo7rFTF2HjVd3lHL74gnMm6CVY180MZHC\n2vaePOFv7i4nPNgUUFq/kcq4xEjmjk/gvf2V+p2Sbv69qXhAmVAUChcdFjsWu4OEyN7OhMgQE53D\nFZQohLhRCPFD/XEakAr8F7hG73INsArYDswVQsQJIaLQtNKbgE+Aa/W+l6N5uBUKhUIxQIpq2xmb\nENGjC0yN1rS4ta2eOur2bhtRoUH9ZoU4Z3IyoUFGPtY10S7ddaKf4iE3zh9HUlQI0WFBpMX4L7ai\n8CQtNozqVjMFdZrRfLm+SQLNoAZN32622vlgfyWXzEgLODBzpHL5zHSKatuRNW389uN8Hvswn6La\n9uGelmKIKW3o5B/rj2K1OwZtzKYOzW8b7yUocTizfLwHnCOE2AS8C3wf+F/gFr0tAXheD0R8EFiN\nFnz4qJSyBVgBmIQQm4E7gZ8O4VwVCoVi1HK0rp3s5BP5klN0D7W3iocug7o/IkODOE+k8NHBauwO\np1uVxP6D38JDTPx++UwevGTKiE3jNtykxYRR1WKmsKGbYJOBKeknPP3TMmKJCQvi86IGVh2spq3b\nxvI5/suuj3QumZGO0QBPflbEu/sqAa04h2J089dPj/D4qgLuW7EPu0O7I9FpsXHp3zbx2o7Skxqz\nUTeo+xZ3igwx0eEny8eQbVullG1onuW+XOil75vAm33a7MBtQzM7hUKh+HLgcDg53tDBEreKgSkx\n/XiozTaiwvz/NFw6M51Vh6rZdbyRhgANaoDzp6QGOnWFF9Jiw9hSVM8RYxC56TG9Sp6bjAYWZCey\nYlcZK3aVMSYunAUTAsvDPZJJigpl0cQkPsirIkhPxVg+wIqSipGF1e5g7eEaxsSF82FeFWFBJv6w\nfCb/XH+Uw1WtrJd1XD9v7IDHbezUPdR9DeoAPNSj+z6QQqFQfMmpbOnCbHX08lBHhwYRFmz0qqEO\nxEMNsGxKCqFBRj46UNWTfzrQkt2Kkyc9Noy2bhsFdXaunesZ1PmjiwRT0mMIMRlYPCnJo9DLaOXy\nWelsLqrnpoXjeHl7qfJQj3K2FTfQarbxx2tncbiqlb+uLcTucLjluveeZ98fLsmHtzzUNkf/unxl\nUCsUCsUopriuA4Ds5BNVCQ0GA6kxYV5zUbd324gOwEPtkn28vbeCMfERxIYHExL0RZc2+PLhykXd\nbXcyc4xnYZic1GgeuDDwgM/RwuWzMiht7OSOJdlskHU+DepVB6uZPiaGzPiIL3iGisFk1cFqIkJM\nnD05mQunptJltfP0hmJCg4x8/axM3thdTqfFRkTIwMxcl+TDWx5qfyiDWqFQKEYxxXVacJa7QQ1a\nYKIvD3VGXGABg/dekENNm5n9Zc3MyAys6p/i1HAP5pyZ5Tsn7peNiJAgfnSRluZsTHy4V8lHRXMX\n33tpNynRobzy7flMSvnybTxGA3aHk9WHajhPpBAWrBm6D148hfiIEFJjQgkPNvH6rnIKa9oDrkbq\noqnTgsloIKaPUyEygLt2yqBWKBSKUUxxfQfRoUEk99E3J8eEei0/3tFtIzJAr05uegxv/2AxzZ2W\nL420YLhJj9Uyz4YGGZjkJuNRnCAzPoJPKqs92l1pHju6bVz39DY+uGdJz+upGDnsK2umvr2bi6af\nyLhsMBj43jlaDvzj9dpduYLq1gEb1I0dVuIjQjyCpgP5TlT35xQKhWIUU1zXwYTkSI8fiNToMGq9\neagDDEp0Jy4ihJgw70VgFIOLK0PLxIQQgkzqJ9wbmfHhNHRY6LT0DiLbU9JEeLCJl+6YT0OHhU1H\n6odphopToai2DYAzfRjLYxMiCA82UVDdNuCxmzosHjmoASJD/Us+1F+jQqFQjECcTie2APKvHqvv\nIDsp0qM9JSaUDouddrfIdafTSbvFRvQoz1s8kgkLNpGTEsWcDKUB9kVmvOZ1ruijo95b2sTMzFhm\nZsYRGmTkSM3ADS7F8FPRbMZoOBFP0Bej0cDk1CjkSRjUjZ0WjxzUEJjkQxnUCoVCMQL5z+ZjTP35\nan785n6O6bc4+9JlsVPR3NUrw4cLV7VEdy91p8WO0xnYj4di+Fh139lcP1Np1n3hCjgsb+piw5E6\nPj5Qhdlq51BlK7PHxWMyGpiUEsURVfxlRFLR1EVqTBjB/dyhmZIWQ0F124ArZjZ2WLxmKwokKFEZ\n1AqFQjECeWNXOTFhwby/v4ob/7XNq7faZWj3DUiEE9USa9xyUbu81QOVfCi+WExGA0ZVGMcnWbqH\nuqShg5+8mce9K/ax6mA1NoeT2WPjAchJiaJIeahHJJXNXWTE9a99F2nRNHZYqGv3zGTUH00dFo8M\nH0BAqUSVQa1QKBQjjOI6rczyD86dyF+vP4PKFjNr82s9+n2klwbP8ZLNwFu1xDazblArD7ViBJMU\nFUpIkJFXd5RR3WrGYnPw0DsHAThzrObZz0mNprLFTJvZOpxTVZwElS3+Deopadp33kBkHw6Hk6ZO\ni0cOaiCg9HvKoFYMKz98Yz+//Th/uKehUIwoVh3SMhhcPD2NZVNSSI8N4+XtJb37HKzmyXVFXH3m\nGCaneko+vFVLdFUCUwb1yMBms/m8pd3fsdGO0WggMy4cWdNGUlQI3146gfZuG+MSI3qqeU5O1Qyu\nwi+Z7KPNbMVi8x97cbricDipajb7Te05NSMGgwH2lTYHPHar2YrD6ZmDGpSHWuGHX394mBe2Hh+0\n8cxWOy2dA9vtr5e1vLajLKDgKoVitOF0Olm5p5xv/ns7C3/7qdesG95YdbCaWVlxZMSFE2Qy8o15\nY9lUWN8j8fjoQBUPvL6PWVlx/ObqGR4ZPkCrlmg0QEvXib/ZdmVQjyi+9a1vsXr1aq/Hbr/9dlat\nWvUFz+j0YYwu+7h6diZ3L8shKSqEhdknyrC7NpmFfmQf5U2dXPXUFo7WjXzDu6XLykV/2cjXn946\nYo3q+o5uLHYHmX481HERIYjUaLYdawh4bFdRF29ZPsKCjfhTWSmD+kvMRweqWX3IM1fnyfLdF3dz\n3TNbA+7fZbFT326hpcvKLj0/qELxZeJgRSsPvK4FFVa1mHvK5vZHeVMneeUtXDztRA7W6+dmEWQ0\ncPtzO7n+ma384OU95KRE8cxNc3oKH/TFYDAQEmTE4raZdRnUKihxZNDY2EhhYSGVlZUe/44ePUp7\n+8g3Ak8WV2Di18/KIiYsmI/vPZtHLp/a67iW6aP/1+hvawvZW9rMu/sqh3S+ZqvdZ3DxYPHYB4ep\najWzr6yZP685MqTXGipcmVv8ST4AFmQnsrukKeDNQ1OnXiXRi+TDYDBwhp+c1gMyqIUQRiGECi0e\nJbR0WanzUnr4ZNh4pI4NR+ooqG6jPsAggIrmE5WsPs2vGZR5KBQjieJ67cf8udvmkpMSxccHq/ye\n86mulb5oWmpPW0pMGI99bTrpcWE0dVi5d1kOb35/Eakx/d8WDQ0y9fqxadc11IGUHlcMPx9++CH3\n3HMPZ511lse/LVu2cOjQoeGe4rBx04Jx/PLKaUxK0TzRydGhvXSwrkwf/Uk+jtV3sHJvBQAbpGeM\nwmDy4Ft5XPK3jTTrRp0/Wrqs/OajfP6+riig/utlLW/sLuf750zkG/PG8vTGo3xeNPLycFc2a3fx\nAjWozVYHeeWByT5cd+tiw73n1H/7B4v7Pd/vt6YQ4kGgCXgFWA80CCG2SSkfCWiGitMSq91Be7eN\n2kEwqB0OJ7/7uIDwYBNdVju7S5q4yM175osyfaeZEBnC2vxa/veyqX7OUChGBhabg5Ag//6K4/Wd\nGAyQlRDBxdPT+Pu6Ihrau0nUdZ4OhxODgV6SjY1H6hibEOGRCu/6eWO5ft7YAc0zJMhIt015qEcq\nV199NTfccAPXXHONx7Hly5czffr0YZjV6cHUjBimZsT022dyajTbin1LAp74tJBgk4Eb54/lxW0l\nvf42B5MD5S28o3vAP8ir4psLxvXbf3dJE995YRcNHRZCg4zcvmSCzztRLv696RhZCeHce0EODgds\nK27gZ28fYNV9Z/s9dyA8vqqAjpYm7so0kxLd/4b+ZKhsDtxDPX9CAqCt9azxCX77m63ad2F4ACny\nvBGIh/pyKeXTwPXAO1LKrwCLTupqimHFanf0RDS36jux5k4r3Tb7KY370cEqDle18ugV0wgxGdkT\noHyjXDeob5g3lmP1HUOmUeu22Xng9X0UjwINnOL0p6i2jem/WM2OY41++5Y0dJAeE0ZYsImLpqXh\ncMJat7s11z2zlV9+cLjnucXmYGtxA2dPThqUuYaYjL3+/pWGemQxdepUxowZM+BjCo1JKVFUtZi9\nejDr2rp5Z18F35w/jmtmZ+J0wqZC/x5dh8PJ7pIm3tlbEVBQqNPp5Dcf5ZMQGUJ2ciQr95T7Pedf\nG4sxGODBS6bQbXP0uykAsDuc7C1t4pzJyYQGmQgPMfHLK6dxvKGTZzYW+71eoFS3mPnH+qO8sLeJ\nJb9bx/6ywAMCA6WiuYvo0CCfXmR34iNDmJIWzbZi/9/FoMluAMKChs6gNgkhjMANwAq9zTMHkxeE\nEOFCiKNCiFuFEGcLITYLIdYJIT4QQsTrfW4UQuwUQmwXQtyutwULIV7W+28QQmSfzOJOheZOS8DS\nhdMdh8PJ23vLWfanDZz7h/U4HE6a3QKRvMk+1h6u4Xsv7sbh8P+FsK6gjsTIEJbPyWRGZmzAeujy\npk5CTEaun5cFwCeHhkb2caS6nZV7KnhtZ9mQjK9QuPPevkosNkdA8QnHGzoYl6jliJ6WEUNWQjir\ndB11Q3s3O4838XnRiR/L3SVNdFrsnJ2TPChzDQ0y9pZ8dNsINhkIDcC7rhh+fvWrX7FgwQKvx375\ny1+ycOHCL3hGI4tLpqeRFBXK1/6+hf/7tLDXsXUFtTiccNXsMcwYE0tCZAjr/cg+Kpu7OPsP67jm\nH59z34p97Dzu/7dwW3EjW4sbuOf8SVx3VhZ7Spv71VJbbA42F9Vz4dQ0bl00ntAgIxuO1PV7jSM1\nbXRY7MwZF9/TtjQnmctmpvPkuqJBczbtK9PW+8MlydidTtYcHvzf9IoAclC7syA7kV0ljQHpqF13\n60KDT+77L5Cz3gaqgcNSyiNCiIeB7QGO/xDg2hr8GbhdSnke8DnwXSFEJPAIcAFwLnC/ECIBzXhv\nllIuAX4N/DbA6w0aP34zjzue3/VFX3bQsTuc/OStPO5fsZ/GDgsNHRaau6y9Ivv7yj7MVjsPv3uQ\nVYeqOdbgP0hif3kzZ2TFYTQamDMungPlLT07vf4ob+piTHw4mfERnDk2jrf3lg9JmieXVnujny8d\nxcjCYnOc8t2VocAVWLglAH1iSUMn45O04CmDwcDF09LYUtRAq9nKzuPaV2dRXXvP39PGwjqCjAYW\nTkz0OeZACOljUHd024gMDfKaFUShGG1kJ0fx6QPncP6UVP685kiv38U1+TVkxIYxNT0Go9HA2TlJ\nbCys79fJ9K9NxVS3mHn8mhkEmwwBxQbtKdWM0OVnZfG1M8dgNMDb/Xipdx1vpL3bxnkimbBgE/Oz\nE/3+trmu4Spq4+Lhy6YSEWLiuy/uHpR83PvKWgg2GVg6PoopadHsD1C7PBC0oi6BS0nmTUjAbHVQ\nUN3qt2+3/j0bOlQeainl41LKFCnlnXrTX6WU9/g7TwgxBZgKfKg31QOuX4F4/fl8YKeUskVK2QVs\nARYDy9AMeYC1etsXyr6yZg5VtozY1DKg3Ur68Zt5vLG7nHuW5fDrqzQ9XWNHd2+DurW3Qf3C1uNU\ntWjC/71+cji2mq0crWtnlh79OmdcPBa7g0OVLX7nV97URaae2ujaOVkcqWknr9z/eQPFJS0pqG4L\nOC2Z4vTnf97Yz3de2D1k4//kzTz+ueHogM4pqm2nsLadrIRwvwG6rWYrDR2WHg81aHmlLXYH6wpq\n2a5LRuwOJ0f01F4bj9Qxe2w80WH+b3cGQmhfDbXZpuQeii8VsRHBfGvxeAD26oan2WpnU2EdF0xN\n7dlcnitSaOywcKDC+29US6eVFTvLuGJWBtfNHcv8CYm95Fu+KKptJz02jKjQIFJjwlg8KYl391f6\ndC6tk7WEmIwsnqTJvs7OSeJoXQflTZ1e+4N2ZysxMoSxCRG92tNiw3jqhtkU13dw/4p9p+zQ2lfW\nxNT0GEJMBmZlxbG/rNnvXW6zVZNkfpjnPyAbAquS6I7Lxqhu8f/bb9a/C8NO0kMdSFDircA9QCxg\nAAxCCKeU0p8M40/AXcAt+vP7gQ1CiCa0IMefAl8H3LdWtUA6kOZql1I6hBBOIUSIlNIj/DU/Px+z\n2Ux+/uAVB2k123u8tmu35zEhIbAgBLPNQbDRgMk4+N6dk1njkfpu3tpTwXUz4rgk087eSs1ztudQ\nIXWdtp5+BwqPM86kfZG0W+z839oyZmeEU1Bn5rP9xUyL8J2nc29VF04nJDhbyc/PJ1rXYH60QxLR\n6T0hjGstJXVtLMiKID8/n8lhDkJNBp5ek8fdCwfndnbP+opPeApXbMzjgokBKZZOicH+TJ5OnC5r\n+/xIDR1WBwcPHR70v7nq5g5W7KrBAMQ7WpiZFtgX+Gt52t/RLTNjeGx9F29szOPcCZ5FVQCKGrTv\nmKCupp7XM8zpJD7cxOtbC6lqs5IWFUR1u421uyXttREcqmzl5jPjT+n1d3//bJZumm3dPc+r6psI\nwn5avL+nwunyGR1KRvMav+i1hVkdGA3wyZ5CUh0N7CjvxGx1MDnyxN9GKnYMwJtbDhMyK95jjBUH\nNDnWBZmaXTI9wcnmog4+3Z5HRoznBti1xoOldaRFmHquc0YibCrsZPXWPMbFe6ZvW5VXzrSUUEqL\nNYlKVpBmFq3YeIBLJ3sPwtxeVEtOQjAFBQUex+KBm86I47k9tazamsd4L9cMBLvDyf7SJi6YFI3Z\nbCbFZKHVbOPTHXlkxvoe82BNFyv3VLFyTwWvbI7gO3OTSIk6YZo2d9kxGSE61ITZ6qCp00qItT3g\nz0dLh2aT5BWWkGXsX4JTXqUdLy48clK/KYG4In4EXAVUBDqoEOJmYKuU8pgQwtX8BHCVlHKLEOKP\nwA/QvNTu+FqBz5Xl5uaSn59Pbm5uoNPzy9ajDYBWdcwcnkRubqbfc1rNVi77v00smZTEb6+eOWhz\ncXEya8zbWQpU8IOLz2BcYiTO2FZYU010Ujpdbd249jLGyHhyc7X36dUdpbRbHPzi6tn8YbXkeJul\n3+t+Vl0EVPHVRTOI03M3jvu0ngpziM/z8vPzGT9xMs3mYmZkZ5CbOwmASwusrM2v4c83Te436vj1\nnWXkV7cSbDJyx5IJPRXffNG1cxeTUhw0d1ooag/m7kH8rPhisD+TpxOnw9qaOiw0dGnBNBEpYz0y\nXobbm/AAACAASURBVJwqaz/YAWhBLX/d1sTH907v+Xz3x561mzkjK47bvjKH/9v2CSVdoT5fq6N5\nlUAFi2dNJjf9xA/hZbPsvLm7nG6bg3vOz+HZzcdockZSbNE2gtcvnU6un+wF/eH+/sVtacFsdfQ8\nN2xuISnGMezv76lyOnxGh5rRvMbhWNuUdY2UdgSRm5vLC/kHiAoN4tpzz+h1+3/mlmYONTo95ma1\nO/hw5WcszUni0sVnABCV2sk/d6zjmCWKZbme/sf8/HyEmEL5KyVcNzejZ8z4DDNPbPuUo92RXJw7\nifKmTtJiwggyGSlt6KSspZjbluaQmztBm7fTyZgNDRS2BvWM0dJpJTZCM+IbOyxUtBZz46Lsnt/a\nvlwU0sBze7YRmzKG3EknF/Asq9vosh3j/FkTCAtr45J5k/jr5xtpC0ns14ba31YKVHHb4vG8sr2U\nXe+Wc/f5k7jr/BwALv7rRiYmR/H3G2frRXiOc8bkseTmBhZwa7M7MLxVqts5k/vtG1NSQJCxmenT\nfGcc273b913RQPza+VLKI1LKDvd/fs65DLhSCLENuAN4GJgtpdyiH18DnAVUonmjXYzR23rahRDB\ngMGbd3qokLrWxmiAw5X+dTcAv/kwn7LGLj7IqzptZCKyup3wYBNZeoL7xCjNIGjosNCsVzRMiAzp\nFZS49WgDydGhzBgTy5lZcRRUt9JpsXkOrrO/rJkJSZG9jA2RGk2RnyAHl67ZdTsG4No5mbSZbT15\ndr3RZbHzk5V5vLK9lP9sPsYDr+/3e5uqolmTlizNSWazHw1cX5xOJ12W00+n+2WnoPrEXZPDVYH9\njQ6EXeWdJEWF8N9b51Lb1s0/1vuXfrR0WTlQ0cKyKSmYjAYWZCeyuR8ddUmD9jcwLrH3bdhLpqdj\ntjpwOrWAmtyMGA5VtvBBXiUTkyPJTR+8Oyweeai7bUSpHNSKLyFzxsWzt7SJ9m4bqw9V92TEcOcc\nkcK+smaPXNGbCuuoa+vm5oXje9qyEiKYnBrV7+9ZZUsXXVZ7T65s0GQYMzNjWXO4hsOVrZz7h/U9\nmX7e0rXVy3JTevobDAYWTUxka3EDdoeTwpo2Zj+2hnf3aT7QvT700+4k6KW2GwPMge0NV0Di/7N3\n3uFxlOfevndXu6qr3qttWX4l23LDBVNcsME0B4fE2IBtSMj5IIEQ4JATIMChphBKTjoBQjG9huZQ\nbMDggnuRbWlkWb33tpK2f3/M7nol7a66VZj7unTZOzuzM++WmWee9/f8ntnJ8sz01NgQgnSaPp0+\nCusN6PzU3HvZdL64cxlLpsXw+Gf5FNS2U9rQQV51m0vyVtbkjBuCfL1kN/w0aqKC/fsl9+wy24Zk\nIeg1oBZC/EEI8RhgFELsEkI8KYR4zPnn60UlSVonSdICSZLOBp4FHgbKhRDOsH8BcBK5uHGBECJc\nCBGCrJX+BvgMWOtYdzXw5aBHOAikmjbCg7TMTAojtx9C9q/z63h9XxlzU8Np67Kwuw8LGyftRgtX\nPb2brSNQCQsg1bQyLS4EtWPqwtn9p9EgdycM8fcjISzAJW+x2+18W9jA2VOiUKlUzE2NwGbHq67Z\nbrdzuKy5V/eg9NgQShoMmH20E3d6ULsH1AsnR6L39/MZhJyqa8duh6fWzeGB1dPZUVDPW/t92ww5\nA+ol06JpMJjYdar/rUhf2VPKwt9sHXBLdYWRxXnTqxrATW9/sdrsHKzqZMm0GGanhLMyK5a3D5R3\nCzw/PFLJDS/s63Yz56zMF/FywHteRjTlTZ3kePn9FNcbiO3RbALk30F4kBadRs3c1HCmJ4RyrLKV\nPUWNXD4rcVgLBj3Z5ike1ArfRc5Ki8BgsvLgB8dpNJi43qGrdmfptBhsHuzzPjhcSViglqXTussV\nL5oez97iRkq8FPcXOJrKuAfUABdmxXG4rJk73jyMxWbntb2l5Ne08fzOIi6aHtet7gLg3KnRtHSa\nOVHZypacaqw2O3/cehKL1ca/D1ei06iZlRzmdewRjmx2k2EoAXUzoQF+TI6Wj02jVpGdFMbhPuqi\nCuvamRQVhEatIik8kIevkGu9PjlWxVf58s1IaWMHdrudUkcSoqcWvC9i9f796rlhtFiH5HDka8tj\nwHHk4PZp4Ijj8XHHcwPlJuAZIcRXwDzgz45CxLuAT5GLDx+UJKkF2Z5PI4TYAdyMrLc+Y+RVtyHi\n9GTFh5Jb1eYzA+r0kJwSHcwLP1pIsE7jsr3qiz9+ns/eokY+Otp3S1Oz1c4jH53g568d4jdbcvsV\n4EnV7UyLO53N0vmp0Qf40Wgw0dxpIixQ6/iiyXduRfUGatuMLJ4i1446A2VnhXBPqlu7qG0zMrvH\nDzU9JgSz1U5Zo/ciiXJXQH36h+GnUbNwcqRPT02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4qfjDxzlUtVlI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Rqffvopx48fx2QyUbVqVSIiIqhSpQplypShTJkyVKlSxdEzHBQUlOvvvr6+xdpjnJGRQXJysqNX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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f08d848aac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 4))\n",
    "births_by_date.plot(ax=ax)\n",
    "\n",
    "# Add labels to the plot\n",
    "ax.annotate(\"New Year's Day\", xy=('2012-1-1', 4100),  xycoords='data',\n",
    "            xytext=(50, -30), textcoords='offset points',\n",
    "            arrowprops=dict(arrowstyle=\"->\",\n",
    "                            connectionstyle=\"arc3,rad=-0.2\"))\n",
    "\n",
    "ax.annotate(\"Independence Day\", xy=('2012-7-4', 4250),  xycoords='data',\n",
    "            bbox=dict(boxstyle=\"round\", fc=\"none\", ec=\"gray\"),\n",
    "            xytext=(10, -40), textcoords='offset points', ha='center',\n",
    "            arrowprops=dict(arrowstyle=\"->\"))\n",
    "\n",
    "ax.annotate('Labor Day', xy=('2012-9-4', 4850), xycoords='data', ha='center',\n",
    "            xytext=(0, -20), textcoords='offset points')\n",
    "ax.annotate('', xy=('2012-9-1', 4850), xytext=('2012-9-7', 4850),\n",
    "            xycoords='data', textcoords='data',\n",
    "            arrowprops={'arrowstyle': '|-|,widthA=0.2,widthB=0.2', })\n",
    "\n",
    "ax.annotate('Halloween', xy=('2012-10-31', 4600),  xycoords='data',\n",
    "            xytext=(-80, -40), textcoords='offset points',\n",
    "            arrowprops=dict(arrowstyle=\"fancy\",\n",
    "                            fc=\"0.6\", ec=\"none\",\n",
    "                            connectionstyle=\"angle3,angleA=0,angleB=-90\"))\n",
    "\n",
    "ax.annotate('Thanksgiving', xy=('2012-11-25', 4500),  xycoords='data',\n",
    "            xytext=(-120, -60), textcoords='offset points',\n",
    "            bbox=dict(boxstyle=\"round4,pad=.5\", fc=\"0.9\"),\n",
    "            arrowprops=dict(arrowstyle=\"->\",\n",
    "                            connectionstyle=\"angle,angleA=0,angleB=80,rad=20\"))\n",
    "\n",
    "\n",
    "ax.annotate('Christmas', xy=('2012-12-25', 3850),  xycoords='data',\n",
    "             xytext=(-30, 0), textcoords='offset points',\n",
    "             size=13, ha='right', va=\"center\",\n",
    "             bbox=dict(boxstyle=\"round\", alpha=0.1),\n",
    "             arrowprops=dict(arrowstyle=\"wedge,tail_width=0.5\", alpha=0.1));\n",
    "\n",
    "# Label the axes\n",
    "ax.set(title='USA births by day of year (1969-1988)',\n",
    "       ylabel='average daily births')\n",
    "\n",
    "# Format the x axis with centered month labels\n",
    "ax.xaxis.set_major_locator(mpl.dates.MonthLocator())\n",
    "ax.xaxis.set_minor_locator(mpl.dates.MonthLocator(bymonthday=15))\n",
    "ax.xaxis.set_major_formatter(plt.NullFormatter())\n",
    "ax.xaxis.set_minor_formatter(mpl.dates.DateFormatter('%h'));\n",
    "\n",
    "ax.set_ylim(3600, 5400);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You'll notice that the specifications of the arrows and text boxes are very detailed: this gives you the power to create nearly any arrow style you wish.\n",
    "Unfortunately, it also means that these sorts of features often must be manually tweaked, a process that can be very time consuming when producing publication-quality graphics!\n",
    "Finally, I'll note that the preceding mix of styles is by no means best practice for presenting data, but rather included as a demonstration of some of the available options.\n",
    "\n",
    "More discussion and examples of available arrow and annotation styles can be found in the Matplotlib gallery, in particular the [Annotation Demo](http://matplotlib.org/examples/pylab_examples/annotation_demo2.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [Multiple Subplots](04.08-Multiple-Subplots.ipynb) | [Contents](Index.ipynb) | [Customizing Ticks](04.10-Customizing-Ticks.ipynb) >"
   ]
  }
 ],
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  "anaconda-cloud": {},
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   "display_name": "Python 3",
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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